Training strategies for attaining transfer of problem-solving skill in statistics: A cognitive-load approach.

TLDR

The study examined whether the type of practice problem influences transfer performance through cognitive load, hypothesizing that conventional problems would increase training effort and reduce transfer. Three computer‑based training strategies—conventional, worked, and completion—were compared by measuring training performance, transfer performance, and cognitive load. Results showed that, aside from training time and effort, the completion and worked strategies yielded higher transfer than the conventional strategy.

Abstract

Studied the differential effect on training performance, transfer performance, and cognitive load for 3 computer-based training strategies. The conventional, worked, and completion conditions emphasized, respectively, the solving of conventional problems, the study of worked-out problems, and the completion of partly worked-out problems. The relation between practice-problem type and transfer was expected to be mediated by cognitive load. It was hypothesized that practice with conventional problems would require more time and more effort during training and result in lower and more effort-demanding transfer performance than practice with worked-out or partly worked-out problems. With the exception of time and effort during training, the results supported the hypothesis. The completion strategy and, in particular, the worked strategy proved to be superior to the conventional strategy for attaining transfer.